code: def _hyp2f1_small_parameters(a, b, c, z):
      """ "Compute 2F1(a, b, c, z) when a, b, and c are small."""
      dtype = dtype_util.common_dtype([a, b, c, z], tf.float32)
      a = tf.convert_to_tensor(a, dtype=dtype)
      b = tf.convert_to_tensor(b, dtype=dtype)
      c = tf.convert_to_tensor(c, dtype=dtype)
      z = tf.convert_to_tensor(z, dtype=dtype)
      numpy_dtype = dtype_util.as_numpy_dtype(dtype)
  
      use_fraction_computation = (
          (tf.math.abs(c) < 1.0)
          & (tf.math.abs(b) < 30.0)
          & (tf.math.abs(c) < 30.0)
      )
      a_fraction = tf.where(
          use_fraction_computation, a, numpy_dtype(0.0)
      )
      b_fraction = tf.where(
          use_fraction_computation, b, numpy_dtype(0.0)
      )
      c_fraction = tf.where(
          use_fraction_computation, c, numpy_dtype(1.0)
      )
      result = _hyp2f1_fraction(a_fraction, b_fraction, c_fraction, z)
  
      a_taylor = tf.where(use_fraction_computation, numpy_dtype(0.0), a)
      b_taylor = tf.where(use_fraction_computation, numpy_dtype(0.0), b)
      c_taylor = tf.where(use_fraction_computation, numpy_dtype(1.0), c)
      return tf.where(
          use_fraction_computation,
          result,
          _hyp2f1_taylor_series(a_taylor, b_taylor, c_taylor, z),
      )
  
file_path: probability/tensorflow_probability/python/math/hypergeometric.py
imports: import functools
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.math import generic
label_desc: Use image node_id 3 for calling a global function with example usage: _hyp2f1_small_parameters(a, b, c, z) and returns: tf